app.py

import gradio as gr
from Study_RAG import answer_pipeline
import os

import gradio as gr

HF_TOKEN = os.getenv('data_bridge_pass')  
hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN, "ZagreusMiura/test1_data")


demo = gr.Interface(
    answer_pipeline,
    [
        gr.Textbox(
            label="Submit Questions Related to Study Programs",
            info = "Questions can include program suggestions, requirements, scholarships, etc.",
            placeholder="Suggest a list of statistics programs in Amsterdam",
        )

    ],
    [
    gr.Textbox(
            label="Response",
            lines=15
        )
    ],
    allow_flagging="manual",  # Enable manual flagging
    flagging_options=["Totally Inaccurate", "Somewhat Inaccurate","Almost Accurate","Completely Accurate"],
    flagging_callback=hf_writer  # Save flagged data to the Hugging Face dataset
    
)

demo.queue().launch()